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1. 发明授权

US07720848B2 Hierarchical clustering with real-time updating 有权
标题翻译：分层聚类与实时更新
公开(公告)号：US07720848B2
公开(公告)日：2010-05-18
申请号：US11391864
申请日：2006-03-29
申请人： Agnes Guerraz , Caroline Privault , Cyril Goutte , Eric Gaussier , Francois Pacull , Jean-Michel Renders
发明人： Agnes Guerraz , Caroline Privault , Cyril Goutte , Eric Gaussier , Francois Pacull , Jean-Michel Renders
IPC分类号： G06F7/00 , G06F17/00
CPC分类号： G06F17/30705 , G06K9/6219 , Y10S707/99942
摘要： A probabilistic clustering system is defined at least in part by probabilistic model parameters indicative of word counts, ratios, or frequencies characterizing classes of the clustering system. An association of one or more documents in the probabilistic clustering system is changed from one or more source classes to one or more destination classes. Probabilistic model parameters characterizing classes affected by the changed association are locally updated without updating probabilistic model parameters characterizing classes not affected by the changed association.
摘要翻译：概率聚类系统至少部分地由指示表征群集系统的类的字数，比率或频率的概率模型参数定义。概率聚类系统中的一个或多个文档的关联从一个或多个源类改变为一个或多个目的地类。表征受改变的关联影响的类的概率模型参数在本地更新，而不更新表征不受改变的关联影响的类的概率模型参数。

2. 发明申请

US20070239745A1 Hierarchical clustering with real-time updating 有权
标题翻译：分层聚类与实时更新
公开(公告)号：US20070239745A1
公开(公告)日：2007-10-11
申请号：US11391864
申请日：2006-03-29
申请人： Agnes Guerraz , Caroline Privault , Cyril Goutte , Eric Gaussier , Francois Pacull , Jean-Michel Renders
发明人： Agnes Guerraz , Caroline Privault , Cyril Goutte , Eric Gaussier , Francois Pacull , Jean-Michel Renders
IPC分类号： G06F7/00
CPC分类号： G06F17/30705 , G06K9/6219 , Y10S707/99942
摘要： A probabilistic clustering system is defined at least in part by probabilistic model parameters indicative of word counts, ratios, or frequencies characterizing classes of the clustering system. An association of one or more documents in the probabilistic clustering system is changed from one or more source classes to one or more destination classes. Probabilistic model parameters characterizing classes affected by the changed association are locally updated without updating probabilistic model parameters characterizing classes not affected by the changed association.
摘要翻译：概率聚类系统至少部分地由指示表征群集系统的类的字数，比率或频率的概率模型参数定义。概率聚类系统中的一个或多个文档的关联从一个或多个源类改变为一个或多个目的地类。表征受改变的关联影响的类的概率模型参数是本地更新的，而不更新表征不受改变的关联影响的类的概率模型参数。

3. 发明授权

US07630977B2 Categorization including dependencies between different category systems 有权
标题翻译：分类包括不同类别系统之间的依赖关系
公开(公告)号：US07630977B2
公开(公告)日：2009-12-08
申请号：US11170033
申请日：2005-06-29
申请人： Eric Gaussier , Jean-Michel Renders , Cyril Goutte , Caroline Privault
发明人： Eric Gaussier , Jean-Michel Renders , Cyril Goutte , Caroline Privault
IPC分类号： G06F17/30
CPC分类号： G06F17/30038 , G06F17/30705 , Y10S707/99935 , Y10S707/99937
摘要： In categorizing an object respective to at least two categorization dimensions each defined by a plurality of categories, a probability value indicative of the object is determined for each category of each categorization dimension. A categorization label for the object is selected respective to each categorization dimension based on (i) the determined probability values of the categories of that categorization dimension and (ii) the determined probability values of categories of at least one other of the at least two categorization dimensions.
摘要翻译：在对对应于由多个类别定义的至少两个分类维度的对象进行分类中，针对每个分类维度的每个类别确定指示对象的概率值。基于（i）确定的分类维度的类别的概率值和（ii）所确定的至少两个分类中的至少另一个的类别的概率值，对于每个分类维度分别选择对象的分类标签尺寸。

4. 发明申请

US20070005639A1 Categorization including dependencies between different category systems 有权
标题翻译：分类包括不同类别系统之间的依赖关系
公开(公告)号：US20070005639A1
公开(公告)日：2007-01-04
申请号：US11170033
申请日：2005-06-29
申请人： Eric Gaussier , Jean-Michel Renders , Cyril Goutte , Caroline Privault
发明人： Eric Gaussier , Jean-Michel Renders , Cyril Goutte , Caroline Privault
IPC分类号： G06F7/00
CPC分类号： G06F17/30038 , G06F17/30705 , Y10S707/99935 , Y10S707/99937
摘要： In categorizing an object respective to at least two categorization dimensions each defined by a plurality of categories, a probability value indicative of the object is determined for each category of each categorization dimension. A categorization label for the object is selected respective to each categorization dimension based on (i) the determined probability values of the categories of that categorization dimension and (ii) the determined probability values of categories of at least one other of the at least two categorization dimensions.
摘要翻译：在对对应于由多个类别定义的至少两个分类维度的对象进行分类中，针对每个分类维度的每个类别确定指示对象的概率值。基于（i）确定的分类维度的类别的概率值和（ii）所确定的至少两个分类中的至少另一个的类别的概率值，对于每个分类维度分别选择对象的分类标签尺寸。

5. 发明授权

US08165974B2 System and method for assisted document review 有权
标题翻译：辅助文件审查的系统和方法
公开(公告)号：US08165974B2
公开(公告)日：2012-04-24
申请号：US12479972
申请日：2009-06-08
申请人： Caroline Privault , Jacki O'Neill , Jean-Michel Renders , Victor Ciriza , Yves Hoppenot
发明人： Caroline Privault , Jacki O'Neill , Jean-Michel Renders , Victor Ciriza , Yves Hoppenot
IPC分类号： G06F15/18 , G06F5/00 , G06F17/00
CPC分类号： G06N5/043 , G06Q10/10 , G06Q50/18
摘要： A system and method for reviewing documents are provided. A collection of documents is portioned into sets of documents for review by a plurality of reviewers. For each set, documents in the set are displayed on a display device for review by a reviewer and temporarily organized through grouping and sorting. The reviewer's labels for the displayed documents are received. Based on the reviewer's labels, a class from a plurality of classes is assigned to each of the reviewed documents. A classifier model stored in computer memory is progressively trained, based on features extracted from the reviewed documents in the set and their assigned classes. Prior to review of all documents in the set, a calculated subset of documents for which the classifier model assigns a class different from the one assigned based on the reviewer's label is returned for a second review by a reviewer. Models generated from one or more other document sets can be used to assess the review of a first of the sets.
摘要翻译：提供了一种审查文件的系统和方法。一组文件分为多组文件供多位评审员审阅。对于每个集合，集合中的文档显示在显示设备上，供审阅者查看，并通过分组和排序进行临时组织。接收到显示文件的审阅者标签。根据审阅者的标签，将来自多个类的课程分配给每个经审查的文档。存储在计算机存储器中的分类器模型基于从集合中的经审查的文档及其分配的类中提取的特征而逐渐训练。在审查集合中的所有文档之前，返回分类器模型分配与基于审阅者标签分配的类别不同的类别的文档的计算子集，供审阅者进行第二次审阅。可以使用从一个或多个其他文档集生成的模型来评估第一组的审查。

6. 发明申请

US20100313124A1 MANIPULATION OF DISPLAYED OBJECTS BY VIRTUAL MAGNETISM 有权
标题翻译：通过虚拟磁场操纵显示对象
公开(公告)号：US20100313124A1
公开(公告)日：2010-12-09
申请号：US12480002
申请日：2009-06-08
申请人： Caroline Privault , Jacki O'Neill , Jean-Michel Renders , Victor Ciriza , Yves Hoppenot , Gregory Bauduin , Ana Fucs , Ye Deng , Gregoire Gerard , Mathieu Knibiehly
发明人： Caroline Privault , Jacki O'Neill , Jean-Michel Renders , Victor Ciriza , Yves Hoppenot , Gregory Bauduin , Ana Fucs , Ye Deng , Gregoire Gerard , Mathieu Knibiehly
IPC分类号： G06F3/01 , G06F3/041
CPC分类号： G06F3/0488 , G06F3/04812
摘要： A computer implemented tactile user interface (TUI) and a method of manipulating objects with a virtual magnet are provided. The TUI includes a display comprising a touch-screen. The display is configured for displaying a set of graphic objects, each graphic object representing a respective one of a set of items, such as documents, e.g., text documents or images. A virtual magnet is caused to move on the display, in response to touching on the touch-screen, e.g., by dragging a finger or other implement across. The magnet is associated with a particular function command such that a subset of the graphic objects exhibits a response to the virtual magnet (e.g., is caused to move, relative to the virtual magnet or exhibits another visible response), each graphic object in the subset moving or otherwise responding as a function of an attribute of the underlying item represented by the graphic object.
摘要翻译：提供了计算机实现的触觉用户界面（TUI）和使用虚拟磁体操纵对象的方法。 TUI包括包括触摸屏的显示器。显示器被配置为显示一组图形对象，每个图形对象表示一组项目中的相应一个，诸如文档，例如文本文档或图像。导致虚拟磁体在显示器上移动，以响应于触摸触摸屏幕，例如通过拖动手指或其他工具跨越。磁体与特定的功能命令相关联，使得图形对象的子集表现出对虚拟磁体的响应（例如，相对于虚拟磁体移动或呈现另一可见响应），子集中的每个图形对象根据由图形对象表示的基础项目的属性的函数移动或以其他方式进行响应。

7. 发明申请

US20100014762A1 CATEGORIZER WITH USER-CONTROLLABLE CALIBRATION 有权
标题翻译：具有用户可控校准的分类器
公开(公告)号：US20100014762A1
公开(公告)日：2010-01-21
申请号：US12174721
申请日：2008-07-17
申请人： Jean-Michel Renders , Caroline Privault , Eric H. Cheminot
发明人： Jean-Michel Renders , Caroline Privault , Eric H. Cheminot
IPC分类号： G06K9/62
CPC分类号： G06K9/6277
摘要： A calibrated categorizer comprises: a multi-class categorizer configured to output class probabilities for an input object corresponding to a set of classes; a class probabilities rescaler configured to rescale class probabilities to generate rescaled class probabilities; and a resealing model learner configured to learn calibration parameters for the class probabilities rescaler based on (i) class probabilities output by the multi-class categorizer for a calibration set of class-labeled objects, (ii) confidence measures output by the multi-class categorizer for the calibration set of class-labeled objects, and (iii) class labels of the calibration set of class-labeled objects, the class probabilities rescaler calibrated by the learned calibration parameters defining a calibrated class probabilities rescaler. In a method embodiment, class probabilities are generated for an input object corresponding to a set of classes using a classifier trained on a first set of objects, and are rescaled to form rescaled class probabilities using a resealing algorithm calibrated using a second set of objects different from the first set of objects. The method may further entail thresholding the rescaled class probabilities using thresholds calibrated using the second set of objects or a third set of objects.
摘要翻译：校准分类器包括：多类分类器，被配置为输出与一组类对应的输入对象的类概率; 类概率重定标器被配置为重新缩放类概率以产生重新缩放的类概率; 以及重新密封的模型学习者，被配置为基于（i）由多类分类器输出的用于类标记对象的校准集的类概率来学习类概率重定标器的校准参数，（ii）由多类输出的置信度度量分类器，用于类标记对象的校准集，以及（iii）类标记对象的校准集的类标签，通过定义校准的类概率重定标器的所学习的校准参数校准的类概率重新计数器。在方法实施例中，针对与使用在第一组对象上训练的分类器相对应的类的集合的输入对象生成类概率，并且使用使用不同对象的第二组对象校准的重新密码算法重新缩放以形成重新缩放的类概率从第一组对象。该方法还可能使用使用第二组对象或第三组对象校准的阈值来限定重新归类的类概率。

8. 发明授权

US09405456B2 Manipulation of displayed objects by virtual magnetism 有权
标题翻译：通过虚拟磁力操纵显示对象
公开(公告)号：US09405456B2
公开(公告)日：2016-08-02
申请号：US12480002
申请日：2009-06-08
申请人： Caroline Privault , Jacki O'Neill , Jean-Michel Renders , Victor Ciriza , Yves Hoppenot , Gregory Bauduin , Ana Fucs , Ye Deng , Grégoire Gerard , Mathieu Knibiehly
发明人： Caroline Privault , Jacki O'Neill , Jean-Michel Renders , Victor Ciriza , Yves Hoppenot , Gregory Bauduin , Ana Fucs , Ye Deng , Grégoire Gerard , Mathieu Knibiehly
IPC分类号： G06F3/00 , G06F3/0488 , G06F3/0481
CPC分类号： G06F3/0488 , G06F3/04812
摘要： A computer implemented tactile user interface (TUI) and a method of manipulating objects with a virtual magnet are provided. The TUI includes a display comprising a touch-screen. The display is configured for displaying a set of graphic objects, each graphic object representing a respective one of a set of items, such as documents, e.g., text documents or images. A virtual magnet is caused to move on the display, in response to touching on the touch-screen, e.g., by dragging a finger or other implement across. The magnet is associated with a particular function command such that a subset of the graphic objects exhibits a response to the virtual magnet (e.g., is caused to move, relative to the virtual magnet or exhibits another visible response), each graphic object in the subset moving or otherwise responding as a function of an attribute of the underlying item represented by the graphic object.
摘要翻译：提供了计算机实现的触觉用户界面（TUI）和使用虚拟磁体操纵对象的方法。 TUI包括包括触摸屏的显示器。显示器被配置为显示一组图形对象，每个图形对象表示一组项目中的相应一个，诸如文档，例如文本文档或图像。导致虚拟磁体在显示器上移动，以响应于触摸触摸屏幕，例如通过拖动手指或其他工具跨越。磁体与特定的功能命令相关联，使得图形对象的子集表现出对虚拟磁体的响应（例如，相对于虚拟磁体移动或呈现另一可见响应），子集中的每个图形对象根据由图形对象表示的基础项目的属性的函数移动或以其他方式进行响应。

9. 发明授权

US07711747B2 Interactive cleaning for automatic document clustering and categorization 有权
标题翻译：自动文档聚类和分类的交互式清理
公开(公告)号：US07711747B2
公开(公告)日：2010-05-04
申请号：US11784321
申请日：2007-04-06
申请人： Jean-Michel Renders , Caroline Privault , Ludovic Menuge
发明人： Jean-Michel Renders , Caroline Privault , Ludovic Menuge
IPC分类号： G06F17/30
CPC分类号： G06F17/3071 , Y10S707/953
摘要： Documents are clustered or categorized to generate a model associating documents with classes. Outlier measures are computed for the documents indicative of how well each document fits into the model. Outlier documents are identified to a user based on the outlier measures and a user selected outlier criterion. Ambiguity measures are computed for the documents indicative of a number of classes with which each document has similarity under the model. If a document is annotated with a label class, a possible corrective label class is identified if the annotated document has higher similarity with the possible corrective label class under the model than with the annotated label class. The clustering or categorizing is repeated adjusted based on received user input to generate an updated model associating documents with classes. Outlier and ambiguity measures are also calculated at runtime for new documents classified using the model.
摘要翻译：文档被聚类或分类以生成将文档与类相关联的模型。对于表示每个文档适合模型的程度的文档，计算异常值度量。基于异常值测量和用户选择的异常值准则，向用户识别异常值文档。对于指示每个文档在模型下具有相似性的类的数量的文档，计算模糊度度量。如果使用标签类注释文档，则如果注释文档与模型下可能的校正标签类具有与标注标签类更高的相似性，则可以识别可能的校正标签类。基于接收到的用户输入重复调整聚类或分类，以生成将文档与类相关联的更新模型。在运行时还使用模型分类的新文档计算异常值和模糊度度量。

10. 发明授权

US08189930B2 Categorizer with user-controllable calibration 有权
标题翻译：具有用户可控校准的分类器
公开(公告)号：US08189930B2
公开(公告)日：2012-05-29
申请号：US12174721
申请日：2008-07-17
申请人： Jean-Michel Renders , Caroline Privault , Eric H. Cheminot
发明人： Jean-Michel Renders , Caroline Privault , Eric H. Cheminot
IPC分类号： G06K9/74 , G06K9/62
CPC分类号： G06K9/6277
摘要： A calibrated categorizer comprises: a multi-class categorizer configured to output class probabilities for an input object corresponding to a set of classes; a class probabilities rescaler configured to rescale class probabilities to generate rescaled class probabilities; and a resealing model learner configured to learn calibration parameters for the class probabilities rescaler based on (i) class probabilities output by the multi-class categorizer for a calibration set of class-labeled objects, (ii) confidence measures output by the multi-class categorizer for the calibration set of class-labeled objects, and (iii) class labels of the calibration set of class-labeled objects, the class probabilities rescaler calibrated by the learned calibration parameters defining a calibrated class probabilities rescaler. In a method embodiment, class probabilities are generated for an input object corresponding to a set of classes using a classifier trained on a first set of objects, and are rescaled to form rescaled class probabilities using a resealing algorithm calibrated using a second set of objects different from the first set of objects. The method may further entail thresholding the rescaled class probabilities using thresholds calibrated using the second set of objects or a third set of objects.
摘要翻译：校准分类器包括：多类分类器，被配置为输出与一组类对应的输入对象的类概率; 类概率重定标器被配置为重新缩放类概率以产生重新缩放的类概率; 以及重新密封的模型学习者，其被配置为基于（i）由多类分类器输出的用于类标记对象的校准集的类概率来学习类概率重定标器的校准参数，（ii）由多类输出的置信度度量分类器，用于类标记对象的校准集，以及（iii）类标记对象的校准集的类标签，通过定义校准的类概率重定标器的所学习的校准参数校准的类概率重新计数器。在方法实施例中，针对与使用在第一组对象上训练的分类器相对应的类的集合的输入对象生成类概率，并且使用使用不同对象的第二组对象校准的重新密码算法重新缩放以形成重新缩放的类概率从第一组对象。该方法还可能使用使用第二组对象或第三组对象校准的阈值来限定重新归类的类概率。

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